A Magnitude/Phase-Locked Loop System Based on Estimation of Frequency and In-Phase/Quadrature-Phase Amplitudes
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Bibliographic record
Abstract
This paper introduces a new phase-locked loop (PLL) system. The proposed system provides the dominant frequency component of the input signal and estimates its frequency. The mechanism of the proposed PLL is based on estimating in-phase and quadrature-phase amplitudes of the desired signal and, hence, has application advantages for communication systems which employ quadrature modulation techniques. The studies demonstrate that the proposed PLL also provides a superior performance for power system applications. Derivation of the mathematical model and theoretical stability analysis of the proposed PLL are carried out using dynamical systems theory. Advantages of the proposed PLL over the conventional PLLs are its capability of providing the fundamental component of the input signal which is not only locked in phase but also in amplitude to the actual signal while providing an estimate of its frequency. Computer simulation is used to evaluate its performance. Evaluations confirm structural robustness of the proposed PLL with respect to noise and distortions.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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